Daniele Fakhoury

PhD Candidate in Mathematics

Mathematics Department
Università di Roma - Tor Vergata
Via della Ricerca Scientifica 1, 00133, Roma
Office n. 1216, Corridor B1
fakhoury@mat.uniroma2.it

Interests

Mathematical aspects of Artificial Intelligence:

Machine Learning: expressivity and explainability of deep neural networks

Computer Science and pure Mathematics in the heart

"Beauty is the first test: there is no permanent place in the world for ugly mathematics"

G. H. Hardy

Teaching

Courses

Current academic year:

Università di Roma Tor Vergata - 2° Semestre 2019-2020: Esercitazioni "Informatica 1" per Matematica. Titolare del corso: Prof.ssa Dora Giammarresi : Course PAGE
Università di Roma Tor Vergata - 2° Semestre 2018-2019: Esercitazioni "Informatica 1" per Matematica. Titolare del corso: Prof.ssa Dora Giammarresi : Course PAGE
Università di Roma Tor Vergata - 1° Semestre 2019-2020: Esercitazioni "Geometria 1" per Ingegneria Medica. Titolare del corso: Prof. Stefano Trapani: Course PAGE

Past academic years:

Università di Roma Tor Vergata - 2° Semestre 2018-2019: Esercitazioni "Analisi Matematica 2" per Scienze e Tecnologie per i Media. Titolare del corso: Prof. Paolo Roselli: Course PAGE
Università di Roma Tor Vergata - 2° Semestre 2017-2018: Esercitazioni "Analisi Matematica 2" per Chimica e Chimica Applicata. Titolare del corso: Prof.ssa Silvia Caprino

Students

No student was harmed in the making of this photo

Geometria 1

Ingegneria Medica (2019-2020)

Analisi 2

Scienze e Tecnologie per i Media (2018-2019)

Analisi 2

Scienze e Tecnologie per i Media (2018-2019)

Curriculum

Education

2015- 2017 - Master degree in Pure and Applied Mathematics - Università di Roma Tor Vergata: cum laude
2011 - 2015 - Bachelor degree in Mathematics - Università di Roma Tor Vergata

Work Experience

2018 - AI Research Internship - Banca d'Italia
2016 - Software Engineer Internship - SinergieIT

Programming Languages & ToolsWork

$\LaTeX$

Full Curriculum
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Research

Pubblications

[3] D. Fakhoury, H. Speleers. On the expressivity of the ExSpliNet model. Under review, 2022. LINK

[2] D. Fakhoury, E. Fakhoury, and H. Speleers. ExSpliNet: An interpretable and expressive spline-based neural network. Neural Networks , 152:332–346, 2022. LINK

[1] Bellomarini, Fakhoury, Gottlob, Sallinger. "Knowledge Graphs and Enterprise AI: The Promise of an Enabling Technology" ICDE 2019 LINK

Visits, schools, workshops & Conferences

SIAM - Conference on Mathematics of Data Science - San Diego, California (September 2022) LINK
Università della Basilicata - Functional Analysis and Numerical Analysis} - Matera - Italy (July 2022) LINK
INdAM Workshop - Geometric Challenges in Isogeometric Analysis - Rome - Italy (January 2020) LINK
Banach Center - Oberwolfach Seminar: Mathematics of Deep Learning - Będlewo - Polland (November 2019) LINK
Scuola Normale Superiore - Mathematical and Computational Aspects of Machine Learning - Pisa - Italy (October 2019) LINK
Max Planck institute for plasma physics - Visiting numerical analysis department - Munich - Germany (June 2018) LINK
Lomonosov State University - Rome Moscow summer school: Matrix Methods and Applied Linear Algebra - Moscow - Russia (Summer 2016) LINK